{"as_of":"2026-08-10T05:35:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9fac11010f2a9eb16786deb66b8c221683d0ede5b4c1735418802b5b84692fa2","coverage":[{"denominator":28,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":28,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T19:20:56.494263Z","state":"measured"},{"denominator":28,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":28,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.17024/citation-record","integrity":"/paper/2607.17024/integrity","json":"/paper/2607.17024/citation-record.json","paper":"/paper/2607.17024"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.7189/jogh.15.04207","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Artificial Intelligence Platform to Predict Children’s Hospital Care for Respiratory Disease Using Clinical, Pollution, and Climatic Factors","venue":"Journal of Global Health","work_id":"8ed61918-dcd9-42a6-abec-a40febb0b923","year":null},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:53.004156Z"},"links":{"citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:7d2f1c71e7020cb821c7cb392d166d2ad0bc91e89a84bf5973cb266cc5c711ea","observation_id":"69c0bdfe-25cb-4197-a514-600c256404c3","resolution":{"observed_at":"2026-08-01T19:23:30.015607Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:20:53.361321Z","title":"Global Climate-Health Impact Tracker (2015-2025)","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:53.361321Z"},"links":{"citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:e16180a59c5c5af451750d4a2fbf8b3a0863fb4e0e9b09e3ba54f0901efc89cc","observation_id":"782ea804-1881-46a6-a025-d4dc377226ba","resolution":{"observed_at":"2026-08-01T19:20:53.361321Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.09620","last_updated":"2023-10-14T17:03:29Z","snapshot_observed_at":"2026-07-06T16:33:04.032904Z","submitted_at":"2023-10-14T17:03:29Z","title":"Machine Learning for Urban Air Quality Analytics: A Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.09620","snapshot_observed_at":"2026-08-01T19:20:53.514372Z","title":"Machine Learning for Urban Air Quality Analytics: A Survey","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:53.514372Z"},"links":{"cited_paper":"/paper/2310.09620","citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:a59d6003c9125150447dc5693f31d5524a8cc4bc1dfe42c3696e12268a01aae3","observation_id":"65b81b98-2ada-43a9-bbac-6920d70d46c2","resolution":{"observed_at":"2026-08-01T19:20:53.514372Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1811.12808","last_updated":"2020-11-11T00:59:17Z","snapshot_observed_at":"2026-07-06T07:18:14.810715Z","submitted_at":"2018-11-13T15:36:42Z","title":"Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1811.12808","snapshot_observed_at":"2026-08-01T19:20:55.726259Z","title":"Rojas, Juan C., John Fahrenbach, Sonya Makhni, et al","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:55.726259Z"},"links":{"cited_paper":"/paper/1811.12808","citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:098bebe272e13381571c97ae005059dc4ff22b2b2bedc4caa2d56d48d476ab78","observation_id":"8f603b7e-f63d-4731-86e7-65646f313f67","resolution":{"observed_at":"2026-08-01T19:20:55.726259Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.09620","last_updated":"2023-10-14T17:03:29Z","snapshot_observed_at":"2026-07-06T16:33:04.032904Z","submitted_at":"2023-10-14T17:03:29Z","title":"Machine Learning for Urban Air Quality Analytics: A Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.09620","snapshot_observed_at":"2026-08-01T19:20:53.629240Z","title":"Houdou, Anass, Imad El Badisy, Kenza Khomsi, et al","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:53.629240Z"},"links":{"cited_paper":"/paper/2310.09620","citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:175e3983741d7a75ef2242457c0dc40baa3bf33a9df0f222aed88dbb5a6b8bb1","observation_id":"ae0bf512-5705-400f-8fff-898c0a0e11a2","resolution":{"observed_at":"2026-08-01T19:20:53.629240Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:20:54.599838Z","title":"A Survey on Bias and Fairness in Machine Learning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:54.599838Z"},"links":{"citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:5acb6bc771d1508ffaf6ff8458ea86d73be2bd47405c348b5faecffef248fcdb","observation_id":"7c3f6157-91f8-4122-81c0-3ed8a80ebb40","resolution":{"observed_at":"2026-08-01T19:20:54.599838Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:20:54.936349Z","title":"Air Pollution Particulate Matter (PM2.5) Prediction in South African Cities Using Machine Learning Techniques","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:54.936349Z"},"links":{"citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:3f36daced7dc008e6c44445b2eaf0db35a1fc0feafee7fb2b69a2d2c06feef34","observation_id":"613a144c-43cc-4095-af0c-b02d3c2223e2","resolution":{"observed_at":"2026-08-01T19:20:54.936349Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.enceco.2025.07.001","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A Systematic Study on PM2.5 and PM10 Concentration Prediction in Air Pollution Using Machine Learning and Deep Learning Model","venue":"Environmental Chemistry and Ecotoxicology","work_id":"3630d9cc-283c-4da1-8507-5303c394d441","year":2025},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:55.165791Z"},"links":{"citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:534ebb8498db71c0ca7d4c6c17a2967d091e7b785f829b9d2cd92ebf99a3f90b","observation_id":"32db1b28-f4cc-4270-9447-9223d26a6175","resolution":{"observed_at":"2026-08-01T19:23:29.670833Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1811.12808","last_updated":"2020-11-11T00:59:17Z","snapshot_observed_at":"2026-07-06T07:18:14.810715Z","submitted_at":"2018-11-13T15:36:42Z","title":"Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1811.12808","snapshot_observed_at":"2026-08-01T19:20:55.531060Z","title":"Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:55.531060Z"},"links":{"cited_paper":"/paper/1811.12808","citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:6f3cef4e0e2d326b935c1eb51a1c668f8c033856c364dbbaad22a62ab6641f75","observation_id":"cf3fab37-674a-4b9a-a111-42116a676956","resolution":{"observed_at":"2026-08-01T19:20:55.531060Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.chest.2022.02.001","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Framework for Integrating Equity Into Machine Learning Models","venue":"CHEST Journal","work_id":"c35ac6e2-9837-4353-b361-1532b18440c3","year":2022},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:55.978777Z"},"links":{"citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:0e001094355da62a4c55b1af1bfaf34985b8442881218d6aeff1229733f71b56","observation_id":"3b5deccd-fead-481b-b360-a014386ea099","resolution":{"observed_at":"2026-08-01T19:23:29.521046Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:20:56.048442Z","title":"Ensemble-Based Classification Approach for PM2.5 Concentration Forecasting Using Meteorological Data","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:56.048442Z"},"links":{"citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:cacf5223e37f665cddff4f8f3e04d5bf9090f4ed5430eef5ca13391acd73fcd2","observation_id":"5d3e7cc5-e646-4851-a596-ca51a1e5b0a5","resolution":{"observed_at":"2026-08-01T19:20:56.048442Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:20:56.121718Z","title":"Fairness of Machine Learning Algorithms for Predicting Foregone Preventive Dental Care for Adults","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:56.121718Z"},"links":{"citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:548aaf1100107991f177be5d64b2ca4d4ebf4f4a4e30ff0df21e5cffce8fb8fb","observation_id":"8c6563ee-0b5b-4ec2-90c6-d7ebdbba05ba","resolution":{"observed_at":"2026-08-01T19:20:56.121718Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1705.07874","last_updated":"2017-11-25T03:53:32Z","snapshot_observed_at":"2026-07-06T05:43:42.722222Z","submitted_at":"2017-05-22T17:38:10Z","title":"A Unified Approach to Interpreting Model Predictions","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1705.07874","snapshot_observed_at":"2026-08-01T19:20:54.242733Z","title":"Lundberg, Scott M., Gabriel Erion, Hugh Chen, et al","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:54.242733Z"},"links":{"cited_paper":"/paper/1705.07874","citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:a3a7b7577b0b657f95654e47d8160cf726d27c05bcadbb817f197ee35366f378","observation_id":"b0f5cbf6-43e6-4d80-8fa1-81044ca68a22","resolution":{"observed_at":"2026-08-01T19:20:54.242733Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.2196/49023","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Practical Considerations and Applied Examples of Cross- Validation for Model Development and Evaluation in Health Care: Tutorial","venue":"JMIR AI","work_id":"6134389e-33ce-4255-9063-22e71a0fd90a","year":null},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:56.315431Z"},"links":{"citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:9b96010092c2b6b3601c3023f36a3993bbfc0328b57172bb4f68b321b299f483","observation_id":"6e4d5d6d-3728-4b04-a421-a7f0e7b033db","resolution":{"observed_at":"2026-08-01T19:23:29.331078Z","resolver_source":"doi_truncated","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:20:56.494263Z","title":"Exploring Machine Learning Algorithms to Predict Acute Respiratory Tract Infection and Identify Its Determinants among Children under Five in Sub-Saharan Africa","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:56.494263Z"},"links":{"citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:8dc05202be2ac22f3cbbe356320e3e738688455f19fe70422cfb8f5d70ddc455","observation_id":"db85c34a-fa3d-4fe6-bbad-36825f71d441","resolution":{"observed_at":"2026-08-01T19:20:56.494263Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:20:56.231107Z","title":"Wilimitis, Drew, and Colin G","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:56.231107Z"},"links":{"citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:8a1b1e42e2ce1816bfdbbd27fd4b0700a80c30c59a1e3099016ca1372e90178d","observation_id":"dd9ea1cc-d854-4c81-bf55-0082c0ea6d24","resolution":{"observed_at":"2026-08-01T19:20:56.231107Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:20:53.187910Z","title":"Chin, Marshall H., Nasim Afsar-Manesh, Arlene S","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":867,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:53.187910Z"},"links":{"citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:1d22a1584ff812d512d0e89ee7e94d2619f9631e4ce2ebbcd78f214cadb20ebc","observation_id":"a13aa351-0fb5-4dee-964f-22b659996342","resolution":{"observed_at":"2026-08-01T19:20:53.187910Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/bioengineering12111276","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Ku, Yunseo, Soon Bin Kwon, Jeong-Hwa Yoon, Seog-Kyun Mun, and Munyoung Chang","venue":"Bioengineering","work_id":"7ae31637-a7d0-4748-99f6-fd1cc3b4ed90","year":null},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":1276,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:53.858319Z"},"links":{"citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:10876e3ca0d08668def3d81da061c6ec0e2fd90bb17469229199d7b5861e4926","observation_id":"c5a730e4-13d9-4b21-83b0-6b0c3cd09784","resolution":{"observed_at":"2026-08-01T19:23:29.818480Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1705.07874","last_updated":"2017-11-25T03:53:32Z","snapshot_observed_at":"2026-07-06T05:43:42.722222Z","submitted_at":"2017-05-22T17:38:10Z","title":"A Unified Approach to Interpreting Model Predictions","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1705.07874","snapshot_observed_at":"2026-08-01T19:20:54.130407Z","title":"A Unified Approach to Interpreting Model Predictions","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:54.130407Z"},"links":{"cited_paper":"/paper/1705.07874","citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:5f878c78f95e0049f3edb81ed6326c47b3aff92b9adb7049e8df84ee989187a7","observation_id":"593b1874-fa65-431c-a7d0-538bd9c825ba","resolution":{"observed_at":"2026-08-01T19:20:54.130407Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:20:55.329831Z","title":"Ensuring Fairness in Machine Learning to Advance Health Equity","venue":null,"work_id":null,"year":1990},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:55.329831Z"},"links":{"citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:6b40661356a4937f9a6c6f1a76c7a3b606f0c18a812b1f8e8173a0e2c0259435","observation_id":"df05ec31-88a3-41be-a286-9cc4255fdc92","resolution":{"observed_at":"2026-08-01T19:20:55.329831Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:20:54.388973Z","title":"From Local Explanations to Global Understanding with Explainable AI for Trees","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:54.388973Z"},"links":{"citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:8333d035626d417d53e08d55b4fb6177ff0fc205a96b4f4c784506a22817bb43","observation_id":"905d2910-a306-48fa-81ab-b76c9ae2f5aa","resolution":{"observed_at":"2026-08-01T19:20:54.388973Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/s42256-021-00373-4","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Machine Learning and Algorithmic Fairness in Public and Population Health","venue":"Nature Machine Intelligence","work_id":"9ed08d1f-e221-4ad7-89da-a8d127ac6b17","year":null},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:54.771725Z"},"links":{"citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:72f4f3158389b3cbf88bc43d05b7fc4e3829d401833d12fef0a1c87c698d7518","observation_id":"5d014b5a-b2dd-42bf-8c40-bb303e430e8b","resolution":{"observed_at":"2026-08-01T19:23:29.745255Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:20:53.965457Z","title":"Machine Learning Models for Predicting the Occurrence of Respiratory Diseases Using Climatic and Air- Pollution Factors","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:53.965457Z"},"links":{"citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:88f2695f4b71ad58d32cbb4e0cb824f92142c1e80260ac4ec49a0cafd482ae14","observation_id":"dd3540d8-154d-4e4d-9455-67cfe89d25de","resolution":{"observed_at":"2026-08-01T19:20:53.965457Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:20:53.259593Z","title":"Guiding Principles to Address the Impact of Algorithm Bias on Racial and Ethnic Disparities in Health and Health Care","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:53.259593Z"},"links":{"citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:9d15aeaf59d54d2b1a51d21119ba73e1a6f5bf11ed388a1f28fa073715d0fded","observation_id":"33162a84-30c7-4489-bb00-e7dde8a15d39","resolution":{"observed_at":"2026-08-01T19:20:53.259593Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.4209/aaqr.230151","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Interpretable Machine Learning Approaches for Forecasting and Predicting Air Pollution: A Systematic Review","venue":"Aerosol and Air Quality Research","work_id":"a9d4b13a-e6ad-4596-ab33-cf3dbc38da0f","year":null},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:53.718655Z"},"links":{"citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:a1c8245201536fbcefad67e65ddcbd0ac85216175a38ae63b90af2ba5f6411a9","observation_id":"5412b131-22b3-47a0-b3ca-ced4cc6ff19a","resolution":{"observed_at":"2026-08-01T19:23:29.926703Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/s41598-025-11260-y","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Prognosis of Air Quality Index and Air Pollution Using Machine Learning Techniques","venue":"Scientific Reports","work_id":"1e1bf82b-d0ec-4e15-8849-9bb8ec59440b","year":null},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:52.850324Z"},"links":{"citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:b618ac33308096f87ab5d5ecfebc888084c8bbfc55d5e6d719ec5e4ad50e17c5","observation_id":"2e2127c9-85f0-498b-b2cb-8e08f3d86943","resolution":{"observed_at":"2026-08-01T19:23:30.256256Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/s41598-024-85089-2","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Cabral-Miranda, William, Cauê Beloni, Felipe Lora, Rogério Afonso, Thales Araújo, and Fátima Fernandes","venue":"Scientific Reports","work_id":"b569588e-b955-4081-9de7-96aed11f23eb","year":null},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":2385,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:52.918111Z"},"links":{"citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:aef96a49b2bf52639db36cbd47221fd291d57c7a515e93c374287f831480a66c","observation_id":"31c9489c-9e93-4a3c-8cb9-cb55306bde6f","resolution":{"observed_at":"2026-08-01T19:23:30.143353Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/s25154864","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Varma, Sudhir, and Richard Simon","venue":"Sensors","work_id":"e5de3ec9-e1f6-493a-bac7-fc736c163884","year":null},"citing_paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis","version":1},"reference_index":4864,"source":"pdf_text","source_observed_at":"2026-08-01T19:20:56.177875Z"},"links":{"citing_paper":"/paper/2607.17024"},"observation_digest":"sha256:e10492a2a852535cf9e136ab05135067e881716f964fa4c0291510b99b3f67ef","observation_id":"97c4d35d-469c-4054-abe1-dbeb0a120169","resolution":{"observed_at":"2026-08-01T19:23:29.439629Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2607.17024","last_updated":"2026-07-19T01:36:30Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-01T19:20:51.717002Z","submitted_at":"2026-07-19T01:36:30Z","title":"Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis"},"reference_resolution":{"displayed":28,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":18,"verified_exact":9,"verified_fuzzy":0},"total_outbound_references":28},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2607.17024."}